Pixar is the gold-standard in storytelling. With their 17 feature films, they’ve redefined how to create animated worlds and compelling characters.

What if you could know the secrets of Pixar’s storytelling success? Now you can. Pixar announced recently that they would team up with Khan Academy to deliver free lessons on how they deliver storytelling magic.

We’re long-time fans of Pixar at Juice because their methods don’t just apply to good storytelling, but to good data storytelling as well.

So far they’ve released two of the six lessons on storytelling, and once again there are some great principles that can be used to improve the narratives you create with your data. We’ve pulled out some of the best tips Pixar uses to create stories that can also apply to your data and data stories.

On Asking the “What If” Question

“Although our movies involve hundreds of people and take years to make, they all begin with a simple idea about some world and character. What if there’s life out there in the universe? What if a rat wanted to cook haute cuisine? What if our toys that are all around us actually were sentient and can come alive? These what if questions invite the imagination into a story we want to explore.”

“The best ‘what ifs’ are questions that sort of feel like a key that unlocks the door.”

Asking “what if” is a great question to ask yourself when you’re first deciding what direction you want to take your narrative. Not only does asking this question guide how you structure your story, but it also allows you to determine what information is most important to your audience and what can be left on the cutting room floor. It can be easy to overwhelm with data; narrowing your focus is the greatest favor you can offer your audience.

Here are some “What If” questions you could apply to your data storytelling:

What If my sales team knew exactly which prospects needed the most attention today?

What If nurses could tell which patients were at risk for sepsis?

What If human resources leaders could explore the complexity of their organization in the same way they explore Google maps, zooming out to see how all the parts connect and zooming in to see what’s going on on the ground?

What If teachers could visually see how each of their students were doing on their learning journey, and quickly identify the knowledge gaps and resources to fill those gaps?

On World

“A ‘what if’ statement is ultimately connected to a world and a character… When we say ‘rule’ what we really mean is the environment, or set of rules in which our story will take place.”

Choosing your world can be most closely associated with the effort to set the context in our data stories. It’s important to ground the audience in the “world” before you start introducing the “characters” - your data. In our data apps, we are careful to set the stage for the audience by explaining the purpose and context before thrusting users into a series of charts.

On Flawed Characters

“Entertaining characters are often deeply flawed...these flaws can also be the key to why audiences care about them.”

This lesson reminds us of “flawed” data points. Often the outliers and the unexpected data points are the most interesting. Sure they don’t tell the whole story, but they definitely give more insight into what’s actually happening with your data and can provide some colorful detail in your data story.

On Fully-Developed Characters

“We call these characters fully developed. This means we’ve gotten to know them so well that we can imagine them in almost any situation.”

Providing full context around the characters in your data allows you to be able to look at your data points from multiple perspectives and draw out three-dimensional insights, an important step in data storytelling.

On Behavioral Characteristics

“We can talk about characters in two ways. They have external features, which is their design, their clothes, what they look like. Then much more interesting is the internal features. Are they insecure, are they brave, are they jealous?”

With this lesson the distinction between descriptive and behavioral data comes to mind. For example, we can look at descriptive data about customers, but really the behavioral data is much more interesting. How do customers react to stimuli? That’s where the real story is.

On Authentic Experiences

“Characters have to come from authentic human emotions and experiences”

When working constantly with numbers, it’s easy to sometimes forget that behind each data point is a living, breathing person. How do you connect the data to the actual real-life actions that are taking place to create that data?

On Story Flow

“What happens when I tell the story to another person, is that these other things show up, without me asking for them, even while I’m telling them. The story starts to come alive. The characters start to come alive. And then also the person you told the story to will tell you what they thought of it, notes, they’re free. They actually are helping you make your story and characters better.”

This is very true of data storytelling. The more you run through the story flow with users, the more insight you receive into how they think about the data they are seeing and what they need to know. Based on this feedback, you can adapt and change the way you present your data to make a better overall experience for your users.

Want to learn more about data storytelling? Check out some of our other resources on the subject: